In relation extraction for knowledge-based question answering, searching from one entity to another entity via a single relation is called "one hop". In related work, an exhaustive search from all one-hop relations, two-hop relations, and so on to the max-hop relations in the knowledge graph is necessary but expensive. Therefore, the number of hops is generally restricted to two or three. In this paper, we propose UHop, an unrestricted-hop framework which relaxes this restriction by use of a transition-based search framework to replace the relation-chain-based search one. We conduct experiments on conventional 1- and 2-hop questions as well as lengthy questions, including datasets such as WebQSP, PathQuestion, and Grid World. Results show that the proposed framework enables the ability to halt, works well with state-of-the-art models, achieves competitive performance without exhaustive searches, and opens the performance gap for long relation paths.
翻译:在获取基于知识的答案时,通过单一关系从一个实体到另一个实体的搜索被称为“一跳”。在相关工作中,对知识图中的所有一跳关系、二跳关系等等进行彻底搜索是必要的,但费用却很高。因此,跳的次数一般限于两三个。在本文中,我们建议UHop是一个无限制的跳框架,它通过使用基于过渡的搜索框架来取代基于关系链的搜索框架来放松这一限制。我们在常规的1-和二跳问题以及包括诸如WebQSP、路径问题和网格世界等数据集在内的冗长问题上进行实验。结果显示,拟议的框架能够停止、配合最先进的模型、在不作彻底搜索的情况下实现竞争性业绩,并为长期关系开辟业绩差距。